Let AI agents do the heavy lifting of FinOps
Azure cost data is overwhelming and the answers are buried. Turbo360 AI agents read your environment, explain what changed and why, and rank the optimization actions worth taking, so your team acts on answers instead of digging for them.
The problem, solved
What teams come to us with
Each pain has a concrete outcome in Turbo360. No waiting on engineering.
Cost data is overwhelming
AI explains what changed and why
Agents read spend across your whole estate and surface the few drivers that actually moved the bill, in language anyone on the team can read.
You do not know what to fix first
Actions ranked by dollar impact
Rightsizing, reservations, and scheduling moves come ranked by what they save, so your team starts with the work that matters most.
Every cost question needs an analyst
Answers without the analyst
See why spend jumped or what a team costs this month in seconds, with no waiting on a report.
Key features
The AI built into your Azure FinOps
A team of FinOps agents
Agents focused on the key FinOps tasks. Point one at a specific problem and it works through the cost data for you.
Explain with AI
Turns raw cost data and analysis into clear insights, so you read what changed and why instead of interpreting rows yourself.
AI anomaly detection
Machine-learned baselines flag unusual spend automatically and route it to the team that owns the workload before it hits the invoice.
AI-assisted forecasting
The Budget Planner projects where spend is heading as a range, so you plan next year’s Azure budget on a forecast instead of a guess.
The agents
A team of agents for the work
FinOps repeats
Each agent owns one job. Point it at a problem and it works through
your cost data, then comes back with the answer and the fix.
Reduce waste
Rightsizing Agent
Reviews a resource and evaluates the rightsizing options, then gives clear guidance and an action plan, with the monthly saving shown for each move.
Investigate
Cost Spike Troubleshooter
Traces a sudden jump in the bill to the resource, service, or change behind it, so you fix the cause instead of digging through exports.
Cut idle time
Scheduling Agent
Judges whether a resource is safe to schedule, then recommends start and stop schedules with a confidence rating, so you pause the right resources outside working hours.
Commit smarter
Reservations Agent
Spots steady, predictable workloads worth a reservation or savings plan and sizes the commitment to the usage it sees.
Model a change
What-If Agent
Answers the questions you would normally hand to an engineer, weighing the considerations for a change you are thinking of making before you commit.
Stay current
Evergreening Agent
Reviews a resource for SKU modernization, surfacing where a newer generation or service tier would serve the same workload better or cheaper.
Explain with AI
Make FinOps a team sport, not a
queue for the expert
There are places across the product where someone looks at a chart or a recommendation and does not fully understand it, so they wait on the FinOps expert to translate it. Explain with AI reads what is in front of you in plain English, with the insights and the actions worth taking, so anyone on the team can act on the data themselves.
Explain with AI
Your amortized Azure cost for May 2026 was £34,633.51, around £1,117 a day. Spend held near £850 a day through the first week, dipped on May 05, then stepped up to about £1,100 from May 11 and stayed there.
Virtual machines are the largest category every day. The rise into the last week is driven mostly by foundry tools, which barely registered early in the month and became a top-three category by May 29.
What you might want to do
- Check what changed around May 11, when daily cost stepped up and held.
- Review the foundry tools growth before it carries into June.
- Look at virtual machines for rightsizing, your largest and steadiest line.
AI anomaly detection
Catch runaway Azure spend
the day it starts
Turbo360 learns what normal looks like for your estate, then watches every day. When spend breaks the expected pattern, an AI
agent
verifies the spike is real and routes it to the owner, so you act before it reaches the invoice.
Learn your normal spend
Machine-learned baselines are built from your historical usage, per subscription, resource group, and service.
Watch spend in real time
Actual cost is compared against the baseline every day, so an unusual spike is caught the day it happens.
Verify and route to an owner
An AI agent confirms the spike is real, not noise, then alerts the team that owns the resource with the dollar impact attached.
Act before the invoice
Drill into the resource, see exactly what changed, and fix it before the cost lands on the bill.
AI-assisted forecasting
Plan next year’s Azure budget on a
forecast, not a guess
The Budget Planner reads your spend history and projects where cost is heading, as a range rather than a single line. You set the plan against it, then watch actuals track the forecast month by month, so the budget conversation starts from evidence.
A ranged forecast
AI projects the months ahead as a high-to-low band, so you plan for the likely range instead of betting on one number.
Plan against the projection
Set a planned cost line on top of the forecast and see the gap, month by month, before you commit the budget.
Track actuals as they land
Actual spend is drawn against the plan and the forecast, so you catch drift early and adjust before year end.
Trusted by leading Azure service provider worldwide
“Turbo360 gives our MSP partners clear visibility into Azure costs, with smarter alerts and proactive management they can pass straight to their customers.”
James Reed
Azure Sales Manager
“Turbo360 is tailored for MSPs like us. It wasn’t just another cost tracking tool-it is built to help us scale FinOps.”
Alex Tilgenkamp
Cloud Architect
FAQ
Common questions
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What can I ask the FinOps agent?
Ask why spend changed, what a team or application costs this period, where waste is hiding, or which optimization to do first. The agent answers from your live environment.
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Do the agents take action automatically?
Agents recommend and rank actions with the dollar impact made clear. You stay in control and apply the ones you approve.
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How are recommendations ranked?
By estimated dollar impact, so your team starts with the moves that save the most, with the trade-off on performance shown for each.
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Is my Azure data used to train external models?
No. Turbo360 connects with read-only access and is independently audited against SOC 2 Type II and ISO 27001.
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